SAE using geospatial data
Nairobi Workshop: Day 4 (geospatial data)
August 26, 2024
Introduction to geospatial data
- One estimate says that 100 TB of only weather data are generated every single day
- This means there is a lot of data to work with!
- Note that this is also problematic, since it can be difficult to work with such large datasets
- Geospatial data is used in a variety of fields
- Agriculture
- Urban planning
- Environmental science
- Public health
- Transportation
- And many more!
The amount of geospatial data is useful for SAE
- Geospatial data can be highly predictive of e.g. poverty
- Urbanity
- Land class/cover
- Vegetation indices
- Population counts
- etc. etc.
- More importantly: it’s available everywhere!
Think of what you need for SAE
- You need a sample, e.g. a household survey
- This will only cover some of the country
- You need auxiliary data that is:
- Predictive of the outcome you care about
- Available throughout the entire country
- Some countries, use administrative data
- But, importantly, it’s often not available or is of low quality!
A quick example
Malawi admin areas - Northern region only
- Survey only lets us say things about the districts!
- What if we want to say something about traditional authorities (TAs)?
- Individual TAs might not have enough observations
- We could use SAE! But what auxiliary data?
Observations at the district and TA level
Sub-area model with sectors